Syllabus
Introduction to Social Media Analytics – Social media data collection – Processing unstructured and semi-structured data – Monitoring user engagement in social media – Identifying Opinions through Sentiment Analysis and Topic Modeling – Social Network Analysis and Metrics – Identifying Influencers in Social Network
Objectives and Outcomes
Course Objectives
- The main objective of the course is to give an introduction to the key concepts about social media text data
- This course introduces machine/deep learning and topic modelling approaches to build a social media text classification model
- This course helps the students to monitor consumers and competitors and glean deeper consumer insights based on advanced social media data modelling
- This courses helps the students to make better business decisions by leveraging social media dat
Course Outcomes
After completing this course, students will be able to
CO1
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Analyze social media text data
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CO2
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Implement a sentiment analysis model using machine/deep learning algorithms
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CO3
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Implement a topic model for social media text categorization
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CO4
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Analyze a social network
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CO-PO Mapping
PO/PSO
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PO1
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PO2
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PO3
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PO4
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PO5
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PO6
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PO7
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PO8
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PO9
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PO10
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PO11
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PO12
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PSO1
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PSO2
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PSO3
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CO
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CO1
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–
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–
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–
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1
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2
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1
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–
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1
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–
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–
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–
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1
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–
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2
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–
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CO2
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2
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2
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2
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2
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2
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–
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–
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1
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–
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–
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–
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2
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3
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2
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1
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CO3
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2
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2
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2
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2
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2
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–
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–
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1
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–
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–
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–
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2
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3
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2
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1
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CO4
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1
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1
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1
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2
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2
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1
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–
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1
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–
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–
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–
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2
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1
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–
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1
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Text Books / References
Text Books / References
Szabo, G., G. Polatkan, O. Boykin & A. Chalkiopoulus, Social Media Data Mining and Analytics, Wiley, ISBN 978-1-118-82485-6, 2019
Golbeck, Jennifer. Analyzing the social web. Newnes, 2013.
Finger, L. & Dutta, S,. Ask, Measure, Learn: Using Social Media Analytics to Understand and Influence Customer Behavior. Sebastopol, CA: O’Reilly, 2014